From dfd983e4e8057630dfafb41e3738e703ed8ef9b4 Mon Sep 17 00:00:00 2001 From: RevathyRamalingam Date: Thu, 16 Oct 2025 21:17:26 +0530 Subject: [PATCH] TypeError when OneHotEncoder object is created --- .../TypeError when OneHotEncoder class is created | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 _questions/machine-learning-zoomcamp/module-4-homework/TypeError when OneHotEncoder class is created diff --git a/_questions/machine-learning-zoomcamp/module-4-homework/TypeError when OneHotEncoder class is created b/_questions/machine-learning-zoomcamp/module-4-homework/TypeError when OneHotEncoder class is created new file mode 100644 index 00000000..2435e1ca --- /dev/null +++ b/_questions/machine-learning-zoomcamp/module-4-homework/TypeError when OneHotEncoder class is created @@ -0,0 +1,11 @@ +TypeError Traceback (most recent call last) +Cell In[60], line 4 +2 scaler = StandardScaler() +3 X_train_num = scaler.fit_transform(X_train_num) +----> 4 ohe = OneHotEncoder(sparse=False) +5 X_train_cat = ohe.fit_transform(df_train[categorical_columns].values) +6 X_train_cat + +You get above error when categorical values are oneHotEncoded using sparse as parameter. This is because in scikit-learn ≥1.2, the OneHotEncoder no longer uses the sparse parameter. Instead, it now uses sparse_output. +So create OneHotEncoder class using spare_output as argument like below, +ohe = OneHotEncoder(sparse_output=False)